AUTHOR=Li Fei , Guo Dagang , Gao Xiaodong , Zhao Xining TITLE=Water Deficit Modulates the CO2 Fertilization Effect on Plant Gas Exchange and Leaf-Level Water Use Efficiency: A Meta-Analysis JOURNAL=Frontiers in Plant Science VOLUME=12 YEAR=2021 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2021.775477 DOI=10.3389/fpls.2021.775477 ISSN=1664-462X ABSTRACT=

Elevated atmospheric CO2 concentrations ([eCO2]) and soil water deficits significantly influence gas exchange in plant leaves, affecting the carbon-water cycle in terrestrial ecosystems. However, it remains unclear how the soil water deficit modulates the plant CO2 fertilization effect, especially for gas exchange and leaf-level water use efficiency (WUE). Here, we synthesized a comprehensive dataset including 554 observations from 54 individual studies and quantified the responses for leaf gas exchange induced by e[CO2] under water deficit. Moreover, we investigated the contribution of plant net photosynthesis rate (Pn) and transpiration rates (Tr) toward WUE in water deficit conditions and e[CO2] using graphical vector analysis (GVA). In summary, e[CO2] significantly increased Pn and WUE by 11.9 and 29.3% under well-watered conditions, respectively, whereas the interaction of water deficit and e[CO2] slightly decreased Pn by 8.3%. Plants grown under light in an open environment were stimulated to a greater degree compared with plants grown under a lamp in a closed environment. Meanwhile, water deficit reduced Pn by 40.5 and 37.8%, while increasing WUE by 24.5 and 21.5% under ambient CO2 concentration (a[CO2]) and e[CO2], respectively. The e[CO2]-induced stimulation of WUE was attributed to the common effect of Pn and Tr, whereas a water deficit induced increase in WUE was linked to the decrease in Tr. These results suggested that water deficit lowered the stimulation of e[CO2] induced in plants. Therefore, fumigation conditions that closely mimic field conditions and multi-factorial experiments such as water availability are needed to predict the response of plants to future climate change.